Description

You will lead data engineering teams and architect cloud-native data solutions on AWS.

This role is on-site.

Responsibilities

• Lead and mentor data engineers and ETL developers, conducting design and code reviews to ensure scalability and security.
• Architect enterprise ETL/ELT pipelines for batch and real-time processing using AWS Glue, Lambda, EMR, and Step Functions.
• Define data modeling standards, metadata management, and governance frameworks for structured and unstructured data.
• Collaborate with stakeholders to define delivery roadmaps and drive Agile/Scrum execution.
• Optimize cloud performance, cost efficiency, and data quality across AWS services like Redshift, S3, and Athena.

Required Skills

• 8+ years of experience in data engineering, ETL development, or data architecture.
• 3+ years of experience leading technical teams in a lead capacity.
• Strong hands-on expertise with AWS data services: Glue, Lambda, S3, Redshift, EMR, Athena, IAM, Step Functions, Lake Formation.
• Deep proficiency in Python, SQL, and PySpark for distributed data processing.
• Experience building ETL/ELT pipelines and data warehousing/lake architectures.
• Proficiency in DevOps practices, CI/CD pipelines (Jenkins, GitHub Actions), and Infrastructure as Code (Terraform/CloudFormation).
• Bachelor’s degree in Computer Science, Engineering, or related field.

Preferred Skills

• AWS Certified Solutions Architect or Data Analytics Specialty.
• Experience in regulated industries (utilities, energy, healthcare, financial services).

Key Skills

Education

Bachelor's degree